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7th Information Systems International Conference, ISICO 2023

作者： Fernanda, Nita Utamima, Amalia Laboratory of Data Engineering and Business Intelligence Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia

scheduling is essential in manufacturing to maintain machinery and increase revenue. Machines that are routinely maintained will boost production, whereas scheduling based on total weighted completion time (TWCT) can improve the performance of production equipment. The Lovebird Algorithm (LBA), Constructive Heuristics (CH), and combination of LBA-CH are used in this study to schedule a single machine with equal processing times. LBA, a population-based algorithm, represents job parts as birds for jobs that can be preempted. The experiments, which used ten jobs divided into dozens of job parts, show that LBA-CH can effectively reduce TWCT compared to CH by 18.16%. © 2023 The Authors. Published by Elsevier B.V.

关键词： scheduling algorithms

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Optimizing Round Robin scheduling with DBSCAN Clustering and Machine Learning

Optimizing Round Robin Scheduling with DBSCAN Clustering and...

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2024 IEEE International Conference on Signal Processing, Information, Communication and Systems, SPICSCON 2024

作者： Hossain, Md Mehrab Biva, Nanziba Khan Nahid, Nafiz Rifat, Ariful Islam Islam, Ashraful Department of Computer Science and Engineering Sylhet Engineering College Sylhet Bangladesh Department of Computer Science and Engineering Faridpur Engineering College Faridpur Bangladesh Department of Computer Science and Engineering American International University Dhaka Bangladesh Department of Computer Science University of Regina Regina Canada

ISBN: (纸本)9798331510213

In the intricate realm of operating systems, scheduling algorithms play a pivotal role in resource allocation and process completion, directly impacting overall system performance. The quest for an efficient and optimized scheduling algorithm is perpetual in the pursuit of optimal operating system utilization. The Round Robin algorithm, known for its robust time-sharing methodology, emerges as a stalwart in the scheduling context. Its versatility spans various domains, making it a preferred choice in both general-purpose computing environments and real-time systems. This study aims to elevate the performance of the Round Robin algorithm in terms of average waiting time and number of context switches without altering its core algorithmic structure. A novel approach is proposed, utilizing DBSCAN to group related processes and determine a more accurate and efficient time quantum. Departing from the conventional practice of using a single time quantum for the entire schedule, we divide the schedule into groups. The optimal time quantum for each group is derived through machine learning and deep learning algorithms, leveraging rigorous features extracted from the schedule. Notably, the LSTM model emerges as the top performer, achieving an impressive 97% accuracy. The proposed modified version consistently outshines its traditional counterpart. In 92% of cases, the modified version demonstrates superior performance in average waiting time while achieving a 96.5% improvement in context switching. Considering both metrics, the modified version showcases a notable enhancement in 87.8% of cases. This holistic assessment unveils a 5% reduction in average waiting time and a substantial 15% decrease in context switching, signifying a meaningful advancement in overall system performance. © 2024 IEEE.

关键词： scheduling algorithms

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Cross-Period Joint scheduling of Task and Network in IEEE 802.1Qbv Time-Sensitive Networks 24

Cross-Period Joint Scheduling of Task and Network in IEEE 80...

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Wang, Pengyu Zhu, Hailong Zhang, Huayu Huang, Tao Beijing University of Posts and Telecommunications Beijing China Purple Mountain Laboratories NanJing China

ISBN: (纸本)9798350363760

Time-sensitive networking introduces deterministic latency and low jitter to Ethernet through traffic shaping mechanisms. The IEEE 802.1Qbv standard ensures deterministic transmission of critical flows via the time-aware shaper, where synthesizing the Gate Control List (GCL) schedule is a core challenge. Most SMT-based schedule synthesis algorithms consider only single-period scheduling under a unified timeline, leading to low schedulability. In this paper, we propose a cross-period scheduling algorithm that jointly schedules task and network, ensuring the correctness of cross-period scheduling constraints under a unified timeline through reasonable period mapping. In our defined task tree model, we introduce an optimization objective to minimize the end-to-end latency of task trees. Finally, we evaluate the performance of our algorithm. The results demonstrate that our algorithm significantly improves schedulability and achieves lower end-to-end latency compared to existing algorithms. Moreover, our algorithm can complete the computation within a reasonable time, even in large-scale networks. © 2024 IEEE.

关键词： scheduling algorithms

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Optimizing Class scheduling for the University of Northern Philippines Using Greedy Algorithm 9

Optimizing Class Scheduling for the University of Northern P...

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9th International Conference on Information Technology and Digital Applications, ICITDA 2024

作者： Querubin, Andrea Nicole Contillo, Gerry L. University of Northern Phillipines Ilocos Sur Vigan City Philippines Mariano Marcos State University Ilocos Norte City of Batac Philippines

ISBN: (纸本)9798331510732

Manual class scheduling at the University of Northern Philippines (UNP) is characterized by inefficiencies, frequent conflicts, and delays, negatively impacting faculty and students. This research explores the development of an automated class scheduling system utilizing the greedy algorithm to address these challenges. The developed system used Agile Methodology to ensure the iterative progress and adaptability, that will allow for ongoing refinements based on the user feedback. The study evaluates current scheduling practices, identifies the appropriate technologies for automation, and designs a web-based application to minimize conflicts and optimize resource allocation. The system uses a greedy algorithm to make locally optimal decisions for globally efficient scheduling. The proposed solution will enhance scheduling accuracy, reduce manual effort, and improve operational efficiency meeting user needs. The proposed system will also manage the conflicts of schedules of the different inputs by its conflict detection and resolution functionality. The research highlights the potential benefits of automated systems in educational settings and offers recommendations for successful implementation. © 2024 IEEE.

关键词： scheduling algorithms

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Hierarchical scheduling Mechanisms in Multi-Level Fog Computing

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IEEE TRANSACTIONS ON SERVICES COMPUTING 2022年第5期15卷 2824-2837页

作者： Maciel Peixoto, Maycon Leone Genez, Thiago A. L. Bittencourt, Luiz F. Fed Univ Bahia UFBA BR-13083970 Sao Paulo Brazil Univ Estadual Campinas UNICAMP Inst Comp BR-13083970 Sao Paulo Brazil European Bioinformat Inst European Mol Biol Lab Wellcome Genome Campus Hinxton CB10 1SD Cambs England

Delivering cloud-like computing facilities at the network edge provides computing services with ultra-low-latency access, yielding highly responsive computing services to application requests. The concept of fog computing has emerged as a computing paradigm that adds layers of computing nodes between the edge and the cloud, also known as micro data centers, cloudlets, or fog nodes. Based on this premise, this article proposes a component-based service scheduler in a cloud-fog computing infrastructure comprising several layers of fog nodes between the edge and the cloud. The proposed scheduler aims to satisfy the application's latency requirements by deciding which services components should be moved upwards in the fog-cloud hierarchy to alleviate computing workloads at the network edge. One communication-aware policy is introduced for resource allocation to enforce resource access prioritization among applications. We evaluate the proposal using the well-known iFogSim simulator. Results suggest that the proposed component-based scheduling algorithm can reduce average delays for application services with stricter latency requirements while still reducing the total network usage when applications exchange data between the components. Results have shown that our policy was able to, on average, reduce the overload impact on the network usage by approximately 11 percent compared to the best allocation policy in the literature while maintaining acceptable delays for latency-sensitive applications.

关键词： Data centers scheduling algorithms Computer architecture Data transfer Dispatching Delays Resource management Fog computing cloud computing Internet of Things allocation

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Dependency-Aware Joint Task Offloading and Resource Allocation in Heterogeneous Mobile Edge Computing

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2024年第12期23卷 19444-19458页

作者： Zhang, Guo Zhang, Baoxian Peng, Shuo Li, Cheng Univ Chinese Acad Sci Res Ctr Ubiquitous Sensor Networks Beijing 100049 Peoples R China Simon Fraser Univ Sch Engn Sci Burnaby BC V5A 1S6 Canada

Mobile edge computing (MEC) is a promising computing paradigm and can effectively reduce the energy consumption and computing costs at mobile devices by offloading computation-intensive and latency-sensitive applications/tasks to edge servers. However, how to achieve cost-effective dependent task offloading and resource allocation subject to application completion time constraint and service configuration constraint at edge side in heterogeneous MEC environments remains a challenge. To address this challenge, in this paper, we study the multi-application dependent task offloading and resource allocation problem in heterogeneous MEC environments for jointly minimizing the energy consumption and computing cost. We first formulate this problem as a mixed integer nonlinear programming (MINLP) problem. We propose a two-stage alternating optimization algorithm. In the first stage, a genetic-based algorithm is proposed to determine an optimized task offloading profile for given transmit power matrix, a look ahead based task scheduling algorithm is designed to obtain an optimized task schedule for the profile. In the second stage, the transmit power allocation problem for a given offloading profile is solved using convex optimization techniques. Extensive simulation results show that the proposed algorithm can effectively reduce the total cost of task executions as compared with baseline algorithms.

关键词： Servers Resource management Costs Energy consumption Optimization Mobile handsets Delays Computational modeling scheduling algorithms Wireless communication Mobile edge computing energy consumption computing cost dependent task offloading resource allocation

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Enhanced Cloud Virtualization Based on Offloading Dynamic Switching scheduling Algorithm Using Optimal Time Desk Task Allocation Model 1st

Enhanced Cloud Virtualization Based on Offloading Dynamic Sw...

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1st International Conference on Intelligent Computing, Smart Communication, and Network Technologies, ICICSCNT 2023

作者： Rajkumar, S. Rahuraman, M.B. Rahul David, M. Sai Senthil Ganapathy, V. Sanjay, S.N. Sona College of Technology Salem India

ISBN: (纸本)9783031759567

Cloud computing provides decentralized process to provide various services, having lot of task running depending of service request the server reach more energy consumption, time to complete task, cause burden. So many virtualized scheduling system task takes virtual allocation to complete the task. But the increasing time leads time consumption to complete the workload in the server. To resolve this problem, we propose an Offloading Dynamic Switching scheduling Algorithm (ODSSA) based on optimal time desk task allocation model to increasing the cloud computing process. Initially the task loading process timing consumption was estimated based on Expected time completion matrix model. Then the time slot is constructed using Min Max Queuing Theory (MMQT). Depends on ETCM and MMQT dynamic switching scheduling algorithm is applied to balance the scheduling task to complete the task using optimal time desk task allocation model. This balances virtual task allocation when the task requires the virtualization task is allocated or other wise to terminate the idle machine to reduce the time and energy consumption. The proposed system achieves high performance compared to the other system as well to allocate the task to reduce the time consumption. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： scheduling algorithms

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Design and Implementation of Packet-Aware scheduling Algorithm for Serverless Architecture 3

Design and Implementation of Packet-Aware Scheduling Algorit...

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3rd International Conference on Artificial Intelligence and Computer Information Technology, AICIT 2024

作者： Chen, Xingliang Gao, Yuan Ding, Yuheng Fu, Peng System Platform R and D Center NARI Group Corporation State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9798350365443

Serverless is a fine-grained deployment model. Users only need to pay for the time segment of specific function execution to achieve true on-demand charging. However, the cloud function startup process requires downloading dependent packages, which delays the response time of the function and reduces the application's ability to respond quickly to load bursts. Therefore, a packet aware scheduling algorithm is proposed for the cloud function cold start problem. The algorithm establishes a scheduling queue and a packet cache tree at the working node. When the server receives the cloud function, the scheduler senses the optimal matching position of the packet through the improved location sensitive hash algorithm (WCFCM-LSH), and schedules the cloud function to the node queue;At the same time, in order to avoid excessive load on the work node, the scheduler will steal the tasks in the highest load scheduling queue and schedule them to other queues to reduce the load of the node. The experiment shows that the packet aware scheduling algorithm can effectively reduce the cold start time of cloud function, improve the scheduling efficiency, and reduce the waste of platform resources. © 2024 IEEE.

关键词： scheduling algorithms

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Research on Ship Crew scheduling Algorithm Based on Improved Grey Wolf Optimization 4

Research on Ship Crew Scheduling Algorithm Based on Improved...

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4th IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Tang, Lin Ying, Wenwei Huang, Meng Zou, Yu Unit 91977 of the Pla Beijing China

ISBN: (纸本)9798350363586

Crew scheduling in civilian ships is a combinatorial optimization problem with various constraints. Traditional methods struggle with large-scale scheduling, while classic algorithms often fail to balance performance and practicality. This paper presents an Improved Grey Wolf Optimization (IGWO) algorithm. We establish a mixed-integer programming model that considers hard and soft constraints to maximize crew-position matching. The IGWO algorithm enhances the standard Grey Wolf Optimization (GWO) framework by integrating strategies like heuristic initialization, adaptive encirclement search, elite leader selection, and constraint violation repair. Simulation on random and real-world datasets show that IGWO outperforms manual methods, rule-based heuristics, and the standard GWO algorithm in objective function value, constraint satisfaction, and employee satisfaction. This research advances heuristic optimization in combinatorial problems. © 2024 IEEE.

关键词： scheduling algorithms

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Design of Task Distribution and scheduling Strategies for Data Processingin the Internet of Things 16

Design of Task Distribution and Scheduling Strategies for Da...

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16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Li, Qiang He, Keqiang Guo, Xing Deqing Alpha Innovation Research Institute University of Science and Technology of China Hefei China School of Computer Science and Technology Anhui University Hefei China Deqing Alpha Innovation Research Institute Anhui University Hefei China

ISBN: (纸本)9798350390643

To adapt to the characteristics of IoT tasks arriving online (i.e., the arrival pattern and time of tasks cannot be pre-dicted), delay sensitivity, and limited processing unit resources, to ensure the completion of tasks with low latency and to ensure the efficient and stable operation of the IoT platform, this paper studies the problem of online task distribution and scheduling in the unit manager of a data-driven Internet of Things (IoT) architecture. The problem is modeled and an efficient online task distribution and scheduling algorithm is proposed, named OnSche. We have validated the performance of the OnSche algorithm using real datasets and conducted a thorough verification. The experimental results show that under different parameter changes, OnSche is consistently superior to the baseline methods. © 2024 IEEE.

关键词： scheduling algorithms

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